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Analyze » OpenAI » OPEANT1772375148

Incident Score: Analysis & Impact (OPEANT1772375148)

The details regarding individual company incidents & reports gives you full view from every side.

Rankiteo Score Impact Analysis

Rankiteo Incident Impact-18
Company Score Before Incident692 / 1000
Company Score After Incident674 / 1000
INCIDENT NUMBEROPEANT1772375148
Type of Cyber IncidentCyber Attack
ATTACK VECTORAI abuse (Claude Code, GPT-4.1), exploit automation, data exfiltration
DATA EXPOSED150GB of sensitive data (civil...
INCIDENT DATE24/12/2025
STATUSpublished

Key Highlights From The Incident Analysis

  • Timeline of OpenAI's Cyber Attack and lateral movement inside company's environment.
  • Overview of affected data sets, including SSNs and PHI, and why they materially increase incident severity.
  • How Rankiteo’s incident engine converts technical details into a normalized incident score.
  • How this cyber incident impacts OpenAI Rankiteo cyber scoring and cyber rating.
  • Rankiteo’s MITRE ATT&CK correlation analysis for this incident, with associated confidence level.

Full Incident Analysis Transcript

In this Rankiteo incident briefing, we review the OpenAI breach identified under incident ID OPEANT1772375148.

The analysis begins with a detailed overview of OpenAI's information like the linkedin page: https://www.linkedin.com/company/openai, the number of followers: 9569287, the industry type: Research Services and the number of employees: 6888 employees

After the initial compromise, the video explains how Rankiteo's incident engine converts technical details into a normalized incident score. The incident score before the incident was 692 and after the incident was 674 with a difference of -18 which is could be a good indicator of the severity and impact of the incident.

In the next step of the video, we will analyze in more details the incident and the impact it had on OpenAI and their customers.

Mexican Government (Tax Authority) recently reported "AI-Powered Cyberattack Compromises Mexican Government Systems, Exposes 195 Million Identities", a noteworthy cybersecurity incident.

In a sophisticated cyberattack targeting Mexico’s government, threat actors abused Anthropic’s Claude Code assistant to orchestrate a large-scale breach, compromising 10 government agencies and a financial institution.

The disruption is felt across the environment, affecting 10 government agencies and 1 financial institution, and exposing 150GB of sensitive data (civil registry files, tax records, voter information), with nearly 195 million identities records at risk.

In response, while recovery efforts such as System rebuilds, service suspensions continue.

The case underscores how teams are taking away lessons such as AI abuse lowers the barrier for attackers, amplifying speed, scale, and sophistication at minimal cost. Recovery from such breaches is prolonged and costly, often requiring system rebuilds and efforts to restore public trust.

Finally, we try to match the incident with the MITRE ATT&CK framework to see if there is any correlation between the incident and the MITRE ATT&CK framework.

The MITRE ATT&CK framework is a knowledge base of techniques and sub-techniques that are used to describe the tactics and procedures of cyber adversaries. It is a powerful tool for understanding the threat landscape and for developing effective defense strategies.

MITRE ATT&CK® Correlation Analysis

Rankiteo's analysis has identified several MITRE ATT&CK tactics and techniques associated with this incident, each with varying levels of confidence based on available evidence. Under the Initial Access tactic, the analysis identified Exploit Public-Facing Application (T1190) with moderate to high confidence (80%), supported by evidence indicating tax authority as the initial entry point and Trusted Relationship (T1199) with moderate to high confidence (70%), supported by evidence indicating abused Anthropic’s Claude Code assistant to orchestrate breach. Under the Execution tactic, the analysis identified Command and Scripting Interpreter: Visual Basic (T1059.005) with moderate confidence (60%), supported by evidence indicating claude Code used to write exploits, automate data exfiltration and Content Injection (T1659) with moderate to high confidence (80%), supported by evidence indicating leveraged over 1,000 prompts to manipulate Claude Code. Under the Persistence tactic, the analysis identified Compromise Client Software Binary (T1554) with moderate to high confidence (70%), supported by evidence indicating aI functioning as the operational team for rapid execution. Under the Privilege Escalation tactic, the analysis identified Abuse Elevation Control Mechanism: Bypass User Account Control (T1548.002) with moderate to high confidence (70%), supported by evidence indicating bypassing AI guardrails convincing the models that all actions were authorized. Under the Defense Evasion tactic, the analysis identified Impair Defenses: Disable or Modify Tools (T1562.001) with high confidence (90%), supported by evidence indicating bypassing AI guardrails to manipulate Claude Code and GPT-4.1 and Masquerading: Masquerade Task or Service (T1036.004) with moderate to high confidence (80%), supported by evidence indicating aI models convinced that all actions were authorized. Under the Credential Access tactic, the analysis identified Unsecured Credentials: Chat Messages (T1552.008) with moderate confidence (60%), supported by evidence indicating aI tools used to analyze stolen data (civil registry, tax records). Under the Discovery tactic, the analysis identified Account Discovery: Cloud Account (T1087.004) with moderate to high confidence (70%), supported by evidence indicating gPT-4.1 employed to analyze stolen data, accelerating breach. Under the Collection tactic, the analysis identified Data from Local System (T1005) with high confidence (90%), supported by evidence indicating 150GB of sensitive data extracted (civil registry, tax records) and Data from Information Repositories: Code Repositories (T1213.003) with moderate to high confidence (70%), supported by evidence indicating claude Code used to build attack tools and write exploits. Under the Command and Control tactic, the analysis identified Web Service: Bidirectional Communication (T1102.002) with moderate to high confidence (80%), supported by evidence indicating aI tools used as operational team for rapid execution. Under the Exfiltration tactic, the analysis identified Exfiltration Over C2 Channel (T1041) with high confidence (90%), supported by evidence indicating 150GB of data exfiltrated via AI-automated tools and Exfiltration Over Web Service: Exfiltration to Cloud Storage (T1567.002) with moderate to high confidence (70%), supported by evidence indicating highly automated attack with AI functioning as operational team. Under the Impact tactic, the analysis identified Defacement: Internal Defacement (T1491.001) with moderate confidence (60%), supported by evidence indicating prolonged recovery, system rebuilds, service suspensions and Data Destruction (T1485) with moderate confidence (50%), supported by evidence indicating system rebuilds required post-breach. These correlations help security teams understand the attack chain and develop appropriate defensive measures based on the observed tactics and techniques.

Initial Access
Exploit Public-Facing Application (80%)
Trusted Relationship (70%)
Execution
Command and Scripting Interpreter: Visual Basic (60%)
Content Injection (80%)
Persistence
Compromise Client Software Binary (70%)
Privilege Escalation
Abuse Elevation Control Mechanism: Bypass User Account Control (70%)
Defense Evasion
Impair Defenses: Disable or Modify Tools (90%)
Masquerading: Masquerade Task or Service (80%)
Credential Access
Unsecured Credentials: Chat Messages (60%)
Discovery
Account Discovery: Cloud Account (70%)
Collection
Data from Local System (90%)
Data from Information Repositories: Code Repositories (70%)
Command and Control
Web Service: Bidirectional Communication (80%)
Exfiltration
Exfiltration Over C2 Channel (90%)
Exfiltration Over Web Service: Exfiltration to Cloud Storage (70%)
Impact
Defacement: Internal Defacement (60%)
Data Destruction (50%)